Here's an unpleasant scenario: You suddenly fall ill while out of town and hurry to the nearest ER. You wisely bring along your prescription pills -- all mixed together in one unmarked bottle -- but are too woozy to remember the names and doses of your medications.

Situations like these make life difficult for ER physicians and other medical professionals, who often are forced to make life-or-death decisions based on scant information about their patients' prescription drug usage. But MedSnap ID, a new subscription service from MedSnap, a Birmingham, Ala.-based startup, aims to improve things by identifying prescription pills visually to improve medication adherence and safety.

"Medication safety is something that's very important and expensive to U.S. healthcare, but it's also something that affects people personally," said Dr. Patrick Hymel, MedSnap's CEO and cofounder, in a phone interview with InformationWeek.

With a background as an ER doctor, Hymel has first-hand knowledge of the problems that MedSnap ID aims to solve.
"I had emergency experiences with patients bringing in pills and not knowing what those pills do," Hymel said. "Trying to get a history from a patient of what they've taken, it's very difficult."

Of course, medical professionals can make medication mistakes too, and these infrequent errors can prove deadly. A distracted doctor, for instance, might write a prescription incorrectly, or a pharmacist might dispense the wrong drug or dosage.

"These types of errors are very difficult to detect if you've got five minutes to talk to a patient in the emergency room," said Hymel.

Most IT teams have their conventional databases covered in terms of security and business continuity. But as we enter the era of big data, Hadoop, and NoSQL, protection schemes need to evolve. In fact, big data could drive the next big security strategy shift.

Why should big data be more difficult to secure? In a word, variety. But the business won’t wait to use it to predict customer behavior, find correlations across disparate data sources, predict fraud or financial risk, and more.